General information and spotify

Column 1

General research question:

This research uses Berlin house music songs categorized in a pre and a post fall of the Berlin wall release date. Therefore the main question of this research is, how did tracks from the genres change because of the fall of the Berlin wall? A comparison between pre and post Berlin wall fall tracks.

Corpus

The corpus exists of a gathering of house tracks from different albums that are made by Berlin artists before and after the fall of the Berlin wall. The chosen time span from release date of the songs is between 10 or 15 years before and 10 or 15 years after the fall (1989).

Decision of choosing the corpus

The decision of choosing this corpus is because I am interested in cultural influences on specific music genres that I like. The interesting part of this case is the change from communism to capitalism in the eastern part of the city which could have a major effect on the music that is listened to in this period of time.

Grouping

At first the different groups in the corpus are the genres house and techno. Second these genres are divided in pre and post fall of the Berlin wall. Third these groups could be divided in eastern Berlin artists and western Berlin artists. The differences among these groups could be that the eastern Berlin artists made through a much bigger cultural change in these years compared to the western Berlin artists. There could be a difference in change or these groups could have created change in the other groups.

Gaps

I think the most important gaps could be the tracks that aren’t on spotify of the smaller groups like eastern - Berlin - pre wall fall - house music. A limitation is that spotify doesn’t provide the popularity of the tracks in the time that they were released because spotify didn’t exist at that time.

An example of an artist and song

Paul Kalkbrenner grew up in eastern Berlin and had the age of 13 when the wall fell. Right after that he started to spin records and became the big dj he is nowadays. Gia 2000 is an example of a typical Paul Kalkbrenner track. Typical about this track is the peaceful vibe that Paul tries to create by the simplicity of the track.

Column 2

Pre Berlin

Post Berlin

Danceability scatter plots

Column 1

Grouped scatter plot

Information

To start the analysis the tracks gathered on spotify are divided into two groups. The green dots represent the tracks that were released before the fall of the Berlin wall and the pink dots represent the period after it.

The first thing that pops out of the image above is that the danceability of post group is higher at the same tempo as the pre group. The second thing we see is that the post group is more concentrated around a bpm of 120-130. Out of this we can conclude that trend of the tracks went to being more danceable could have been created by a change of bpm in the tracks.

The graphs above are interactive. This means it’s possible to hover over all the elements zoom in on parts of the graph.

Column 2

Non grouped scatter plot

Information

To make this trend towards more danceable music in the tempo region of 120-130 pm more visual a trendline is added to the first image in the second image. It is now viewable the the this region of bpm dominates the danceability.

Out of the two graphs on this page we can conclude that there has been an change in tempo in between the groups and that the post group has found the sweet sport of spotify’s danceability parameter in a better way. Next up on the other scatter plots page we are going to look if this change has resulted in a grow of popularity and if there is a difference in other parameters in between the groups.

Other scatter plots

Column 1

Grouped scatter plot

Information

In the graph above shows the correlation between loudness and energy of the tracks that are shown. When seeing the graph a conclusion can be made that for both groups energy increases when loudness increases. The correlation is linear in both groups. The linear increase between loudness and energy looks exactly the same in both groups.

In contrast with the danceability versus tempo the fall didn’t change the fundimental priciple of an increasing loudness with an increasing energy. The next graph will look at the data in an completely different way while sticking with the scatter plots.

Column 2

Album scatter plot

Information

In the graph above the data is organised in a different way. Instead of making the pre and post groups the data is divided into all 58 albums that the data contains. In the graph is shown if the popularity of the albums within the data has increased over time. With the fall of the Berlin wall being in 1989 a difference in popularity is shown. The main difference in popularity between the two periods are the most populair albums. Before the fall of the Berlin wall popularity doesn’t rise above 30 while after it the highest popularity increases to 40 and above fast. The reason for this could be that house and techno music became more mainstream after 1989.

Before the fall of the Berlin wall these music genres were underground and mostly illegal in eastern Berlin. This supports the grow of the popularity after the fall of the Berlin wall. For now the scatterplots are done. Next up are the special plot types which illuminate the data in a couple of other ways.

Boxplot & 3D

Column 1

Boxplot pre

Boxplot post

Column 2

3D plot

Information

In the boxplots at the left is visibile how the diversity and the mean in the tempo differs from pre to post. A cause of this could be that the group of musiscians that made house music before the fall of the Berlin wall was much smaller. Artists had their own way of making music and didn’t look to a music genre that was mainstream at that time.

After the fall of the Berlin wall house music became more mainstream in Berlin which caused the artists to work in a desired frame subconscious. Here above all of the parameters that we have been speaking of are put together in a graph which makes it easy to see where the clusters from the combined graphs are. The 3D plot includes all of de data.

Novelty & tempo

Column 1

Novelty and tempo diagrams

Pre

#### Post

### Tempograms

Pre

Post

Column 2

The tracks

Information

The first graph at the top left shows the novelty function with loudness over time from a track from Klaus Schulze that was released before the fall of the Berlin wall. The graph underneath from a track from Ellen Allien which is released after the fall shows the difference in novelty in between the two tracks. Klaus produced a track with much more variety in it where Ellen produced a track which is more predictable. The change in variety is typical for the transition house music made during this period.

On the second tab the tempograms for both tracks are being showed. This supports the patterns in difference troughout both tracks.

Dendogram & Heatmap

Column 1

Dendogram

Information

Column 2

Heatmap

Information

Chromagrams

Column 1

Key 1

Information

Column 2

Key 2

Information

Self-similarity matrices

Column 1

Self_similarity matrix 1

Information

Column 2

Self_similarity matrix 2

Information

Chordograms

Column 1

Chordogram 1

Information

Column 2

Chordogram 2

Information